Efficiency-of-Neural-Archit.../gpu_power_func.py

54 lines
1.8 KiB
Python

import os
import re
import pickle
import numpy as np
def get_sample_of_gpu():
from re import sub, findall
import subprocess
from subprocess import run
no_graph = "NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running."
no_version = "Failed to initialize NVML: Driver/library version mismatch"
smi_string = run(['rocm-smi', '-P', '--showvoltage', '--showmemuse'], stdout=subprocess.PIPE)
smi_string = smi_string.stdout.decode('utf-8')
smi_string = smi_string.split("\n")
smi_string = list(filter(lambda x: x, smi_string))
if smi_string[0] == no_graph:
raise Exception("It seems that no AMD GPU is installed")
elif smi_string[0] == no_version:
raise Exception("rocm-smi version mismatch")
else:
results= []
gpuW0 = findall("[0-9]*\.[0-9]*",smi_string[2])
gpuW1 = findall("[0-9]*\.[0-9]*",smi_string[4])
gpuM0 = findall("[0-9]+",smi_string[7])
gpuM1 = findall("[0-9]+",smi_string[9])
gpuV0 = findall("[0-9]+",smi_string[13])
gpuV1 = findall("[0-9]+",smi_string[14])
results.append(float(gpuW0[0]) + float(gpuW1[0]))
if len(gpuM0) == 2 and len(gpuM1) == 2:
results.append(int(gpuM0[1]) + int(gpuM1[1]))
elif len(gpuM0) == 2:
results.append(gpuM0[1])
elif len(gpuM1) == 2:
results.append(gpuM1[1])
results.append(int(gpuV0[1]) + int(gpuV1[1]))
return results
#for l in smi_string:
#temp = findall("[0-9]*MiB | [0-9]*W",l)
#if temp:
#return temp
def total_watt_consumed(pickle_name):
with (open(pickle_name, "rb")) as file:
while True:
try:
x = pickle.load(file)
except EOFError:
break
x = np.array(x)
x = x[:,0]
y = [float(re.findall("\d+.\d+",xi)[0]) for xi in x]
return sum(y)